Around the around AI world we go, in 31 projects.
AI innovation and rapid prototyping reached new heights in early 2025 when creative leads Jenny Nicholson and Allister Hercus completed Lab31, an ambitious project to release 31 AI-powered applications in 31 days. The project leveraged multiple AI platforms including OpenAI‘s suite, Anthropic‘s Claude, Google’s Gemini 2.0, and others to demonstrate the potential of AI-assisted development.
Project Overview: Lab31 showcased a diverse range of creative applications that push the boundaries of AI implementation.
- Shame Roulette enables anonymous secret sharing between users
- Creative Seance allows users to receive AI-generated creative feedback in the style of historical figures
- Golf Sim 2.0 provides an interactive virtual golfing experience
- Life Stats offers playful estimations of life experiences like potential romantic admirers or accidental bug consumption
- The Attention Audit extension analyzes browsing patterns to track daily focus
- Pocket Guide serves as an audio companion describing surroundings to reduce screen dependency
Development Approach: The creators emphasized that ideation, not technical implementation, proved to be the most challenging aspect of the project.
- The team treated AI models as collaborative partners, explaining project concepts and seeking guidance on execution
- This approach enabled rapid development, reducing project timelines to hours rather than days or weeks
- The methodology proved effective even for creators lacking traditional development backgrounds
Key Insights: The project revealed important lessons about effective AI collaboration and development practices.
- Experimental approaches often yield unexpected successes, even when initial feasibility seems uncertain
- AI models respond best to precise, well-articulated requests
- Detailed communication with AI models consistently produces more nuanced and useful responses
- The development process benefits from treating AI as a tool for novel solutions rather than just automating existing processes
Looking Forward: Nicholson and Hercus’s work suggests that future success in AI development may depend more on creative problem-solving abilities than technical expertise or familiarity with specific AI tools.
The project’s rapid pace and diverse outputs demonstrate how AI can accelerate the development process while enabling creators to pursue previously impractical ideas. This hints at a future where the barrier to entry for creating sophisticated applications may be more about creative vision than technical knowledge.
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